Example notebooks

jitr includes a growing collection of example notebooks that demonstrate how to use the library in various contexts, which live in examples/notebooks/.

Every notebook also runs in Google Colab: click the Open in Colab badges below.

Start here

• Quickstart compiles a solver for \(\alpha\) + \(^{44}\)Ca, defines a parametric optical potential, and fits it to real elastic scattering data, all in under a minute.

• Bayesian calibration extends the quickstart to a full Bayesian calibration which reveals shell effects in \(\alpha\) + \(^{40,44,48}\)Ca. Includes construction of an error model which is jointly inferred with the optical model parameters, and checking the posterior predictive against the data using empirical coverages.

• Bayesian calibration with multimodal posteriors extends the quickstart to a tempered Bayesian calibration for \(\alpha\) + \(^{48}\)Ca, providing a Bayesian perspective of the famous discrete parameter ambiguity in the binding of the interaction between nuclei and light ions.

Other useful examples

• Reactions and kinematics introduces the Reaction class and shows how to use it to store useful information about the reaction of interest, and how to use it to compute kinematic quantities.

• Koning-Delaroche neutron elastic scattering shows how to compute the elastic scattering cross section for neutrons on various targets using the built-in Koning-Delaroche optical potential in jitr.

• Compare built-in uncertainty-quantified optical potentials walks through posterior sampling, solver setup, and interval construction for several of the built-in uncertainty quantified optical potentials in jitr.

• Analyzing power of the quasi-elastic (p,n) reaction pulls nine angular distributions from EXFOR, solves the coupled Lane channels for the charge-exchange transition to the isobaric analog state, and propagates the KDUQ, WLH and CHUQ posteriors through to the analyzing power, an observable that depends almost entirely on the isovector spin-orbit potential.

• Tabulated neutron and proton densities shows how to grab the tabulated nuclear densities in jitr.

• JLM and JLMB semi-microscopic optical-potentials converts the original JLM example into a notebook and walks through folded microscopic potentials, Lane trends, and tabulated self-energy usage.

• Compare global optical-potential radial forms provides a quick visual comparison of the radial forms of the built-in global potentials in jitr.

• Visualize global optical potential volume integrals shows how to compute and visualize volume integrals for the built-in global optical potentials in jitr.

• Channel-radius convergence study for elastic scattering shows how to check for numerical convergence in realistic calculations.

• Dispersive optical model shows how to use the built-in dispersive optical model in jitr

• UQ demo with Koning-Delaroche potential demos propagating the uncertainty of the built-in KDUQ interaction.

• Optical potential interface shows how to define a custom optical potential using a common interface, and how to use it in a calculation.

• Transmission coefficients by partial wave performs uncertainty quantification for partial wave transmission coefficients

• Mass-model effects on transmission-coefficient uncertainty explores how mass-model choices propagate into transmission coefficients.